Opportunity: Assurance and Resilience through Explainable Zero-Trust Security

Zero-trust is a security model that rigorously verifies every user and device before granting access to resources. Within cloud environments, this principle dictates that no entity, whether internal or external, is trusted by default. While offering robust security, practical implementation often relies on complex technologies like public-key infrastructure and zero-knowledge proofs. This challenge is magnified when Artificial Intelligence (AI) is used to automate security decisions, as the “”black-box”” nature of many models creates an implicit trust that contradicts the core “”never trust, always verify”” tenet.
This research topic seeks novel approaches to: 1) enabling warfighters to securely outsource private data and computation to untrusted clouds with mission assurance and verifiable correctness; 2) improving the resilience of mission-critical applications by distributing them across multiple heterogeneous cloud providers to prevent single points of failure; 3) optimizing the trade-off between strict zero-trust security and performance for time-sensitive missions; and 4) ensuring that any AI used to enforce the security framework is itself explainable, verifiable, and trustworthy. Research topics of interest include, but are not limited to:
•Explainable and Verifiable AI for Zero-Trust Policy Enforcement: Research into AI/ML models that not only automate access control and threat detection but also provide verifiable proof of their reasoning, ensuring the security framework itself is auditable and does not rely on “”black-box”” decisions.
•Decentralized identity and access control mechanisms and protocols, including those that support anonymity.
•Novel cryptographic primitives and protocols with application to zero-trust and AI-driven security paradigms.
•Design of cross-cloud, privacy-aware protocols that integrate with emerging zero-trust security mechanisms and provide verifiable attestations of AI behavior.
•End-to-end data protection, concurrency, and consistency for multi-user, multi-cloud environments.
•Access patterns and volume leakage prevention for oblivious data stores under malicious security.
•Verification and authentication schemes for AI-driven query evaluation over encrypted and unencrypted data.